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Women in Computing & Data Science at Berkeley

We help female and non-binary students at UC Berkeley improve their technical skills and receive mentorship and networking opportunities from industry professionals.

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Home: Welcome

Our Committees

 
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Home: Committees
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Machine Learning

The Machine Learning Committee will complete some introductory and intermediate ML courses to learn concepts, such as Model Validation, Random Forests, Cross Validation, and more! It will also work on one or two mini projects towards the end of the semester using Python to analyze real-world datasets, build practical intuition behind ML, and gain applicable ML skills.

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The prerequisites for the committee are at least Data 8 and/or an introductory CS course. However, other factors besides course experience will be considered as well, so we encourage anyone interested to apply.

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If you're interested in joining this committee for the Spring 2025 semester, please apply here. Applications are due on Friday, February 14th at 11:59PM PT!

Data Science

The Data Science Committee will cover a variety of topics, such as Intro to SQL and Pandas, Data Visualization, Feature Engineering, Data Cleaning, and more! It will also work on one or two mini projects towards the end of the semester using Python & SQL to analyze real-world datasets, find solutions to worldwide issues, and enhance their programming skills.

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The prerequisites for the committee are at least Data 8 and/or an introductory CS course. However, other factors besides course experience will be considered as well, so we encourage anyone interested to apply.

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If you're interested in joining this committee for the Spring 2025 semester, please apply here. Applications are due on Friday, February 14th at 11:59PM PT!

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Project

The Project Committee will complete an advanced technical project using a combination of Data Science and Machine Learning concepts. The members will collaborate and work in groups to clean and visualize the provided datasets using Python, improve their analytical and technical skills, and present their findings in a final deliverable at the end of the semester.

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The prerequisites for the committee are at least Data 8 and/or an introductory CS course and Data 100. However, other factors besides course experience will be considered as well, so we encourage anyone interested to apply.

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If you're interested in joining this committee for the Spring 2025 semester, please apply here. Applications are due on Friday, February 14th at 11:59PM PT!

Home: About

About WiCDS

 

Throughout a majority of her time at UC Berkeley, Co-Founder & Co-President Isabel Zavian always desired to start a club for women interested in pursuing a career in the tech industry to improve their technical skills and receive mentorship and career opportunities from female professionals. She reached out to Co-Founder & Co-President Kyna Ha to share her vision and convinced her to join the team and pursue the idea. After a couple of tireless weeks throughout January of 2021, Women in Computing and Data Science at Berkeley was finally established and registered as an official UC Berkeley student organization. 

"Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the realms of data and uses it strategically will win."

Angela Ahrendts | Former Senior VP of Retail at Apple, Inc.

Join Us

We offer general and lifetime memberships for those interested in joining Women in Computing and Data Science at Berkeley. By becoming a member, you are welcome to attend multiple WiCDS events and receive exclusive access to our resources and opportunities.

General Membership

General membership is open to everyone and allows general members to receive our weekly newsletter and attend general WiCDS events.

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Becoming a WiCDS general member is simple: sign up here!

Become involved in our Committees

Committee members meet weekly throughout the semester and have the opportunity to develop their skills and knowledge through hands-on learning and experiences. This semester, we offer 3 types of committees: Data Science, Machine Learning, and Project. Click here to learn more about them!

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